Installation

Quick install with an LLM agent

If you are setting up Wren AI Core with an AI coding agent (Claude Code, Cursor, Aider, etc.), the fastest path is to install the full Wren AI skills package and let the agent drive the rest. Skills are structured workflow guides that teach AI coding agents how to use the Wren CLI — they are optional but strongly recommended.

# Via npx
npx skills add Canner/WrenAI --skill '*'

# Or via install script
curl -fsSL https://raw.githubusercontent.com/Canner/WrenAI/main/skills/install.sh | bash

The installer auto-detects your AI agent. To target a specific one:

npx skills add Canner/WrenAI --skill '*' --agent claude-code

This installs all four skills into your agent's skill directory:

Skill	Purpose
wren-onboarding	Entry point — handles install, project scaffolding, profile setup, first query
wren-generate-mdl	Schema discovery and MDL project generation from a connected database
wren-usage	Day-to-day query workflow — context, recall, SQL, store results
wren-dlt-connector	Connect SaaS APIs (HubSpot, Stripe, Salesforce, GitHub, Slack, …) into DuckDB via dlt

Then start a new agent session (skills are loaded at session start) and ask:

Use the wren-onboarding skill to install and set up Wren AI Core.

The wren-onboarding skill drives the rest of the setup — environment checks, project scaffolding, data source connection via .env, and a first query — and dispatches to the other skills as needed. Skill source: github.com/Canner/WrenAI/tree/main/skills

See the Skills reference for what each skill does in detail.

If you'd prefer to install manually, follow the steps below.

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Requirements

• Python 3.11+
• pip (or any Python package manager)

Optional, depending on your workflow:

• Git — for cloning skill repositories
• Node.js / npm — for installing skills via npx
• An AI coding agent (Claude Code, Cursor, Windsurf, Cline, etc.) — for skill-driven workflows

Install the CLI

pip install "wren-engine[main]"

This installs:

• wren CLI — query, plan, validate, build, profile, and memory commands
• memory — LanceDB-backed schema indexing and NL-SQL recall
• interactive — terminal-based interactive prompts
• ui — browser-based profile configuration form

Verify the installation:

wren version

Data source extras

DuckDB is included by default. For other databases, add the corresponding extra:

# Single data source
pip install "wren-engine[postgres,main]"

# Multiple data sources
pip install "wren-engine[postgres,bigquery,main]"

Data source	Extra	Notes
DuckDB	(included)	No extra needed
PostgreSQL	postgres
MySQL	mysql
BigQuery	bigquery	Requires Google Cloud credentials
Snowflake	snowflake
ClickHouse	clickhouse
Trino	trino
SQL Server	mssql
Databricks	databricks
Redshift	redshift
Oracle	oracle
Athena	athena	Requires AWS credentials
Apache Spark	spark

Install skills

Skills are structured workflow guides that teach AI coding agents how to use the Wren CLI. They are optional but strongly recommended.

# Via npx
npx skills add Canner/WrenAI --skill '*'

# Or via install script
curl -fsSL https://raw.githubusercontent.com/Canner/WrenAI/main/skills/install.sh | bash

The installer auto-detects your AI agent. To target a specific one:

npx skills add Canner/WrenAI --skill '*' --agent claude-code

The installer drops these skills into your agent's skill directory:

Skill	Purpose
wren-onboarding	End-to-end install + first-connection flow. Triggers on /wren-onboarding, "install wren", "set up wren engine"
wren-generate-mdl	One-time setup — database introspection, type normalization, MDL generation
wren-usage	Day-to-day workflow — schema context, query recall, SQL execution, result storage
wren-dlt-connector	Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack) via dlt pipelines into DuckDB, then auto-generate a Wren project

After installation, start a new agent session — skills are loaded at session start.

See Skills Reference for details on what each skill does.

Virtual environment (recommended)

Keep wren-engine and its dependencies isolated from your system Python:

python3 -m venv ~/.venvs/wren
source ~/.venvs/wren/bin/activate
pip install "wren-engine[postgres,main]"

Activate the environment in every new terminal session before running wren commands:

source ~/.venvs/wren/bin/activate

Upgrading

pip install --upgrade "wren-engine[main]"

To update skills:

curl -fsSL https://raw.githubusercontent.com/Canner/WrenAI/main/skills/install.sh | bash -s -- --force

What's next

• Quickstart — try the CLI with a sample dataset
• Connect Your Database — set up your own data source